Digital Technologies for Public Health Services after the COVID-19 Pandemic: A Risk Management Analysis

Abstract

Digitalization has become an important part of human lives that occurs in many fields, ranging from education to labor. Artificial intelligence is one of the most important disruptive technologies, which has produced massive changes in current medical practices, such as MRI, X-ray, and surgeries. AI-based surgeries present lower risks to patients and support medical specialists when it comes to burnout and more challenging operations, which can be more easily performed with the help of robots. The COVID-19 pandemic had a huge impact on healthcare systems due to the large number of patients that overburdened medical healthcare professionals and the medical capacities of hospitals. In this paper, we approach AI-based tools, which have a significant impact on various specializations in medicine under the form of robots, based on an extensive literature review. The research methods consist of a quantitative study conducted on a sample of 50 nurses with the purpose of assessing the awareness of nurses regarding digital technologies used in the medical field, focusing mainly on their capacity to classify digital technological risks that may occur in a public healthcare system. The results show that most of the respondents (62%) are aware of digital applications used in hospitals and are able to classify and manage the risks that may occur. After conducting our research, we found that nurses have a certain degree of reluctance when it comes to the introduction of digital technologies in the medical field.

Transformative Potential of AI in Healthcare: Definitions, Applications, and Navigating the Ethical Landscape and Public Perspectives

“…(f) Personalized Medicine: AI may help tailor therapies based on individual genetic information and patientspecific data [36], improving the success rates in cancer treatments, for instance [37]. (g) Risk Assessment and Prognostication: AI can process historical and real-time data to identify high-risk patients, predict disease progression, and inform clinical decision-making [38][39][40]. (h) Telemedicine and Virtual Health Assistants: AI can provide assessments and basic healthcare recommendations, improving access to healthcare services [41,42].…”

Examining The Interplay of Technology Readiness and Behavioural Intentions in Health Detection Safe Entry Station

“…Rapid developments in health detection technology reflect a significant evolution in the approach to health care (Komalasari, 2023). This phenomenon creates a strong foundation for research and development in the health sector, bringing about profound changes in the way we approach the diagnosis, treatment, and monitoring of health conditions (Văduva et al, 2023). Despite rapid progress, current health detection still has several limitations.…”

Effects of Visual Communication Design Accessibility (VCDA) Guidelines for Low Vision on Public and Open Government Health Data

“…In the past, the possession of information was the criterion for judging individual abilities, but in modern society, the ability to judge the quality of information has become a necessity [ 3 , 4 ]. When an epidemic such as COVID-19 occurs, “face-to-face” encounters decrease and “untact” encounters inevitably increase [ 5 , 6 ]. In this situation, the information gap of low-vision people, who are disadvantaged regarding access to information, will be further widened, and as a result, they may be exposed to various disadvantages [ 7 , 8 ].…”